Edit model card

base_model:

  • microsoft/mpnet-base

Dataset :

  • sentence-transformers/all-nli
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("ayoubkirouane/Mpnet-base-ALL-NLI")
# Run inference
sentences = [
    'a baby smiling',
    'The boy is smiling',
    'The girl is standing.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
Downloads last month
10
Safetensors
Model size
109M params
Tensor type
F32
·
Inference API
This model can be loaded on Inference API (serverless).